RE: covariates
From: "Nick Holford" n.holford@auckland.ac.nz
Subject: RE: [NMusers] covariates
Date: Thu, September 16, 2004 11:28 pm
Leonid,
Allometry is beyond guesswork. It is one of the best understood and experimentally
tested pieces of quantitative biology known. Please take a look at these papers:
West GB, Brown JH, Enquist BJ. The fourth dimension of life: fractal geometry and
allometric scaling of organisms. Science 1999;284(5420):1677-9.
West GB, Brown JH, Enquist BJ. A general model for the origin of allometric scaling
laws in biology. Science 1997;276:122-26.
Gillooly JF, Brown JH, West GB, Savage VM, Charnov EL. Effects of Size and
Temperature on Metabolic Rate. Science 2001;293:2248-2251.
I agree that one should probably centre on the median WT in the popln but in our
experience this has not made any difference to the estimates. We prefer to report
results per 70 kg for comparison with much more widely available adult values. I
think one should rely on the allometric weight model first then try to explain the
remaining variability with more empirical possibilities e.g. age. This provides a
rational basis for disentangling the strong correlation between weight and age. See
these papers for examples:
Bouwmeester NJ, Anderson BJ, Tibboel D, Holford NH. Developmental pharmacokinetics
of morphine and its metabolites in neonates, infants and young children. Br J
Anaesth 2004;92(2):208-17.
van der Marel CD, Anderson BJ, van Lingen RA, Holford NH, Pluim MA, Jansman FG, et
al. Paracetamol and metabolite pharmacokinetics in infants. Eur J Clin Pharmacol
2003;59(3):243-51.
Anderson BJ, van Lingen RA, Hansen TG, Lin YC, Holford NHG. Acetaminophen
developmental pharmacokinetics in premature neonates and infants: a pooled
population analysis. Anesthesiology 2002;96(6):1336-45.
I disagree with this assertion "if the model without WT describes data better than
the one with WT (you can check it via OF or just looking on the fit) then it make no
sense to use allometric scaling in the model".
It is not unexpected that the OFV might get worse by adding WT. But this does not
invalidate the underlying biology. If you don't put WT in the model then it becomes
problematic for extrapolation from adults to children. At least by standardizing
parameter values to adult values it then becomes obvious how to extrapolate outside
the observed weight range. IMHO it makes no sense to conclude on the basis of
inadequate design (e.g. limited weight range) that WT has no influence on parameter
values when the prior biological knowledge is overwhelming.
I suggest you look at Ribbing & Jonsson before advocating the use of OFV based tests
for empirical covariate searches.
Ribbing J, Jonsson EN. Power, Selection Bias and Predictive Performance of the
Population Pharmacokinetic Covariate Model. Journal of Pharmacokinetics and
Pharmacodynamics 2004;31(2):109-134
Nick